Oncotarget, Vol. 7, No. 40
www.impactjournals.com/oncotarget/
Research Paper
Identification of candidate anti-cancer molecular mechanisms of Compound Kushen Injection using functional genomics Zhipeng Qu1, Jian Cui1,*, Yuka Harata-Lee1,*, Thazin Nwe Aung1, Qianjin Feng2, Joy M. Raison1, Robert Daniel Kortschak1, David L. Adelson1 1
Department of Genetics and Evolution, School of Biological Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia
2
Shanxi Modern Chinese Medicine Engineering Laboratory, Shanxi University of Traditional Chinese Medicine, Shanxi 030619, China
*
These authors contributed equally to this work
Correspondence to: David L. Adelson, email: [email protected] Keywords: systems biology, traditional Chinese medicine, lncRNA, transcriptome Received: March 02, 2016 Accepted: August 24, 2016 Published: September 01, 2016
ABSTRACT Compound Kushen Injection (CKI) has been clinically used in China for over 15 years to treat various types of solid tumours. However, because such Traditional Chinese Medicine (TCM) preparations are complex mixtures of plant secondary metabolites, it is essential to explore their underlying molecular mechanisms in a systematic fashion. We have used the MCF-7 human breast cancer cell line as an initial in vitro model to identify CKI induced changes in gene expression. Cells were treated with CKI for 24 and 48 hours at two concentrations (1 and 2 mg/mL total alkaloids), and the effect of CKI on cell proliferation and apoptosis were measured using XTT and Annexin V/Propidium Iodide staining assays respectively. Transcriptome data of cells treated with CKI or 5-Fluorouracil (5-FU) for 24 and 48 hours were subsequently acquired using high-throughput Illumina RNA-seq technology. In this report we show that CKI inhibited MCF-7 cell proliferation and induced apoptosis in a dose-dependent fashion. We integrated and applied a series of transcriptome analysis methods, including gene differential expression analysis, pathway over-representation analysis, de novo identification of long non-coding RNAs (lncRNA) as well as co-expression network reconstruction, to identify candidate anti-cancer molecular mechanisms of CKI. Multiple pathways were perturbed and the cell cycle was identified as the potential primary target pathway of CKI in MCF-7 cells. CKI may also induce apoptosis in MCF-7 cells via a p53 independent mechanism. In addition, we identified novel lncRNAs and showed that many of them might be expressed as a response to CKI treatment.
on global gene expression changes in different types of cancers in vivo or in vitro [4–6]. The current challenge is to integrate these new techniques to discover or evaluate novel cancer therapies [7]. Traditional Chinese Medicines (TCMs) are experience-based remedies derived from hundreds or thousands of years of clinical use in China. Most TCMs are extracted from one or more medicinal herbs. The existence of multiple bioactive ingredients makes many TCMs potential novel resources for the discovery of new cancer drugs, such as multi-targeted cancer drugs [8]. Compound Kushen Injection (CKI, also known as Yanshu injection) is a State Administration of Chinese Medicine-
INTRODUCTION The complexity of carcinogenesis at the genetic level has been investigated more and more deeply by leveraging fast-developing omics-related techniques in the past decades [1–3]. Novel genetic mutations and molecular markers are now comprehensively identified in cancer genome sequencing projects. More importantly, whole transcriptome analyses are much more widely used to identify novel cancer-related transcripts or regulatory elements, such as long non-protein-coding RNAs (lncRNAs) and alternative splicing, and are also used to characterise the underlying molecular mechanisms based www.impactjournals.com/oncotarget
66003
Oncotarget
approved TCM formula used in the clinical treatment of various types of cancers in China [9, 10]. It is extracted from the roots of two medicinal herbs, Kushen (Radix Sophorae Flavescentis) and Baituling (Rhizoma smilacis Glabrae), using modern standardised Good Manufacturing Processes (GMP) [11, 12]. The chemical fingerprint of CKI contains at least 8 different components, with primary compounds Matrine and Oxymatrine [12]. This indicates that multiple compounds in CKI may deliver an integrated anti-tumor effect through multiple targets and their associated molecular pathways. By detecting the expression of key genes or proteins in single molecular pathways, the anti-tumor effects of Matrine or Oxymatrine, including the inhibition of cell proliferation and induction of apoptosis, have been demonstrated in various types of cancer [13–17]. The molecular mechanisms of CKI as a system have also been recently explored [11, 18]. Quantitative detection of expression changes of key regulators, including betacatenin, CyclinD1 and c-Myc, of the canonical Wnt/ beta-catenin pathway, have shown that CKI can suppress the stem cells in MCF-7 cells by down-regulating this signalling pathway [11]. In addition, other studies suggest that CKI can inhibit mouse sarcoma growth and reduce tumor-induced hyperalgesia via the AKT and TRPV1 signalling pathways by reducing the phosphorylation of ERK and AKT kinases and BAD [18]. The main goal of modern pharmacology is to elucidate the molecular mechanisms that can be targeted by therapeutic compounds. Analyses using purified single components of TCM can be somewhat useful, but are limited when it comes to identifying integrated systemic effects resulting from a multi-compound formula. Furthermore, previous studies attempting to understand the mode of action of CKI have only focused on single or a few molecular pathways by assessing the expression of key regulators in these pathways. We have therefore, taken advantage of high throughput whole transcriptome analyses, and applied these to explore the system wide molecular mechanisms targeted by TCM. We have identified a comprehensive list of expressed genes perturbed by CKI, and used gene expression data to characterise molecular pathways potentially targeted by CKI in MCF-7 human breast cancer cells. Our results show that CKI can alter the expression of many cancer relevant genes and lncRNAs, correlated with the inhibition of cell proliferation through cell cycle arrest and the induction of apoptosis via p53 independent pathways.
CKI. The proliferation of MCF-7 cells was dramatically inhibited when treated with a high dose of CKI (2 mg/ mL, based on the total alkaloid concentration in CKI) and showed a dose-dependent effect (Figure 1A and Supplementary Figure 1A). An Annexin V/Propidium Iodide (PI) assay was used to quantify cell apoptosis when MCF-7 cells were treated with CKI. Percentage of apoptotic cells, particularly at the higher dose of CKI, was increased at both time points compared with untreated cells, indicating that apoptosis was induced in cells treated with CKI (Figure 1B and 1C). The caspase3/7 colorimetric assay also showed that there was increased caspase3/7 activity in cells treated with CKI (Supplementary Figure 1B). Altogether, these results showed that CKI could inhibit growth and induce apoptosis of MCF-7 cells in vitro.
Global gene expression changes in MCF-7 cells treated with CKI To further investigate the underlying molecular mechanisms of CKI on MCF-7 cells, we performed high-depth next generation sequencing using an Illumina HiSeq 2500. In total, more than 732 million stranded 100 basepairs (bp) paired-end reads were sequenced from 9 groups of MCF-7 cells treated with two doses of CKI or one dose of chemotherapy drug 5-Fluorouracil (5-FU) for 24 and 48 hours along with untreated cells (Supplementary Table 1) (GSE78512). The global gene expression profiles of CKI treated cells, particularly in cells treated with high dose CKI (2 mg/mL), were clearly different from the profile of 5-FU treated cells compared with untreated cells (Supplementary Figure 2). We then used edgeR to identify the statistically significant differentially expressed (DE) genes for the pairwise comparisons between cells treated with 1 mg/mL CKI, 2 mg/mL CKI and 5-FU for 24 or 48 hours respectively (Figure 2 and Supplementary Table 2). Compared with untreated cells, fewer than 200 genes had significantly altered expression in cells treated with low dose CKI (1 mg/mL) for 24 or 48 hours (Figure 2A and 2B). However, many more DE genes (1,826 genes for 24 hours and 2,904 for 48 hours) were identified in cells treated with high dose CKI (2 mg/mL). Interestingly, when comparing the number of DE genes in cells treated with high dose CKI with low dose CKI, we observed almost twice as many genes down-regulated but only a small number of genes (828 to 791) up-regulated (Figure 2A and 2B). Furthermore, we compared DE genes in cells treated with high dose CKI and in cells treated with 5-FU (Supplementary Figure 3). For up-regulated genes in cells treated with high dose CKI for 24 hours, approximately half (396 out of 791) of these were also identified as DE genes, with most (384) being upregulated in 5-FU treated cells as well. 459 down-regulated genes were also shown as DE genes with most of these (424 out of 459) also being down-regulated in cells treated with 5- FU for 24 hours (Supplementary Figure 3A). After cells were treated with CKI or 5-FU for 48 hours, the number
RESULTS CKI inhibits MCF-7 cell proliferation and induces cell apoptosis To characterise the effect of CKI on proliferation of MCF-7 breast cancer cells, we used the XTT assay to measure cell viability after treating with different doses of www.impactjournals.com/oncotarget
66004
Oncotarget
of DE genes decreased dramatically in 5-FU treated cells, but greatly increased in cells treated with 2 mg/mL CKI (Supplementary Figure 3B). The common DE genes altered by CKI or 5-FU showed consistent expression changes at 48 hours (Supplementary Figure 3B). To validate the gene expression changes from transcriptome analysis, we performed quantitative PCR (qPCR) for 6 genes and acquired overall consistent results (Figure 2C, Supplementary Figure 4 and Supplementary Table 2).
GO terms were clustered into several primary categories, including “Regulation of biological process, cellular process and metabolic process”, “Cell differentiation, development”, “Transport, localisation”, “Chromatin organisation, organelle organisation”, “Cell motility and migration” and “Secondary metabolic processes and reactive oxygen species metabolic”. Interestingly, we found that the majority of cell growth or proliferation related GO terms included more down-regulated genes, while GO terms associated with “Secondary metabolic processes and reactive oxygen species metabolic” showed enrichment of more up-regulated genes (Figure 3A). In MCF-7 cells treated with CKI for 48 hours, similar categories of over-represented GO terms seen at 24 hours were also observed, such as “Metabolic process”, “Regulation of metabolic process” and “Localization”. In addition, cell proliferation related terms, including “Cell cycle”, “Cell growth” and “Cell death” were also overrepresented in DE genes from cells treated with CKI for 48 hours (Figure 3B). Furthermore, we compared the overrepresentation of GO terms of the 200 most significantly
Annotation of the molecular pathways altered by CKI in MCF-7 cells Since CKI likely contains multiple bioactive ingredients, we used a number of systems biology methods to explore the molecular mechanisms of CKI. The over-represented Gene Ontology (GO) terms for all DE genes identified in cells treated with high dose CKI (2 mg/mL) for 24 hour and 48 hours are shown in Figure 3A and 3B. Based on their functional similarity, these
Figure 1: CKI inhibits proliferation and induces apoptosis of MCF-7 cells. A. Inhibition of MCF-7 cell proliferation with CKI
treatment. The level of viability of cells under different treatments was measured using XTT:PMS. Data are represented as mean ±SEM (n=6). B. and C. Induction of apoptosis in MCF-7 cells with CKI treatment. The level of apoptosis was determined by measuring the levels of Annexin V and PI staining: B) Percentages of Annexin V+/PI+ cells, and C) representative plots of Annexin V and PI staining. Data are represented as mean ±SEM (n=6). Statistical analyses were performed using A) two-way ANOVA or B) t-test comparing with “untreated” (*p
www.impactjournals.com/oncotarget/
Research Paper
Identification of candidate anti-cancer molecular mechanisms of Compound Kushen Injection using functional genomics Zhipeng Qu1, Jian Cui1,*, Yuka Harata-Lee1,*, Thazin Nwe Aung1, Qianjin Feng2, Joy M. Raison1, Robert Daniel Kortschak1, David L. Adelson1 1
Department of Genetics and Evolution, School of Biological Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia
2
Shanxi Modern Chinese Medicine Engineering Laboratory, Shanxi University of Traditional Chinese Medicine, Shanxi 030619, China
*
These authors contributed equally to this work
Correspondence to: David L. Adelson, email: [email protected] Keywords: systems biology, traditional Chinese medicine, lncRNA, transcriptome Received: March 02, 2016 Accepted: August 24, 2016 Published: September 01, 2016
ABSTRACT Compound Kushen Injection (CKI) has been clinically used in China for over 15 years to treat various types of solid tumours. However, because such Traditional Chinese Medicine (TCM) preparations are complex mixtures of plant secondary metabolites, it is essential to explore their underlying molecular mechanisms in a systematic fashion. We have used the MCF-7 human breast cancer cell line as an initial in vitro model to identify CKI induced changes in gene expression. Cells were treated with CKI for 24 and 48 hours at two concentrations (1 and 2 mg/mL total alkaloids), and the effect of CKI on cell proliferation and apoptosis were measured using XTT and Annexin V/Propidium Iodide staining assays respectively. Transcriptome data of cells treated with CKI or 5-Fluorouracil (5-FU) for 24 and 48 hours were subsequently acquired using high-throughput Illumina RNA-seq technology. In this report we show that CKI inhibited MCF-7 cell proliferation and induced apoptosis in a dose-dependent fashion. We integrated and applied a series of transcriptome analysis methods, including gene differential expression analysis, pathway over-representation analysis, de novo identification of long non-coding RNAs (lncRNA) as well as co-expression network reconstruction, to identify candidate anti-cancer molecular mechanisms of CKI. Multiple pathways were perturbed and the cell cycle was identified as the potential primary target pathway of CKI in MCF-7 cells. CKI may also induce apoptosis in MCF-7 cells via a p53 independent mechanism. In addition, we identified novel lncRNAs and showed that many of them might be expressed as a response to CKI treatment.
on global gene expression changes in different types of cancers in vivo or in vitro [4–6]. The current challenge is to integrate these new techniques to discover or evaluate novel cancer therapies [7]. Traditional Chinese Medicines (TCMs) are experience-based remedies derived from hundreds or thousands of years of clinical use in China. Most TCMs are extracted from one or more medicinal herbs. The existence of multiple bioactive ingredients makes many TCMs potential novel resources for the discovery of new cancer drugs, such as multi-targeted cancer drugs [8]. Compound Kushen Injection (CKI, also known as Yanshu injection) is a State Administration of Chinese Medicine-
INTRODUCTION The complexity of carcinogenesis at the genetic level has been investigated more and more deeply by leveraging fast-developing omics-related techniques in the past decades [1–3]. Novel genetic mutations and molecular markers are now comprehensively identified in cancer genome sequencing projects. More importantly, whole transcriptome analyses are much more widely used to identify novel cancer-related transcripts or regulatory elements, such as long non-protein-coding RNAs (lncRNAs) and alternative splicing, and are also used to characterise the underlying molecular mechanisms based www.impactjournals.com/oncotarget
66003
Oncotarget
approved TCM formula used in the clinical treatment of various types of cancers in China [9, 10]. It is extracted from the roots of two medicinal herbs, Kushen (Radix Sophorae Flavescentis) and Baituling (Rhizoma smilacis Glabrae), using modern standardised Good Manufacturing Processes (GMP) [11, 12]. The chemical fingerprint of CKI contains at least 8 different components, with primary compounds Matrine and Oxymatrine [12]. This indicates that multiple compounds in CKI may deliver an integrated anti-tumor effect through multiple targets and their associated molecular pathways. By detecting the expression of key genes or proteins in single molecular pathways, the anti-tumor effects of Matrine or Oxymatrine, including the inhibition of cell proliferation and induction of apoptosis, have been demonstrated in various types of cancer [13–17]. The molecular mechanisms of CKI as a system have also been recently explored [11, 18]. Quantitative detection of expression changes of key regulators, including betacatenin, CyclinD1 and c-Myc, of the canonical Wnt/ beta-catenin pathway, have shown that CKI can suppress the stem cells in MCF-7 cells by down-regulating this signalling pathway [11]. In addition, other studies suggest that CKI can inhibit mouse sarcoma growth and reduce tumor-induced hyperalgesia via the AKT and TRPV1 signalling pathways by reducing the phosphorylation of ERK and AKT kinases and BAD [18]. The main goal of modern pharmacology is to elucidate the molecular mechanisms that can be targeted by therapeutic compounds. Analyses using purified single components of TCM can be somewhat useful, but are limited when it comes to identifying integrated systemic effects resulting from a multi-compound formula. Furthermore, previous studies attempting to understand the mode of action of CKI have only focused on single or a few molecular pathways by assessing the expression of key regulators in these pathways. We have therefore, taken advantage of high throughput whole transcriptome analyses, and applied these to explore the system wide molecular mechanisms targeted by TCM. We have identified a comprehensive list of expressed genes perturbed by CKI, and used gene expression data to characterise molecular pathways potentially targeted by CKI in MCF-7 human breast cancer cells. Our results show that CKI can alter the expression of many cancer relevant genes and lncRNAs, correlated with the inhibition of cell proliferation through cell cycle arrest and the induction of apoptosis via p53 independent pathways.
CKI. The proliferation of MCF-7 cells was dramatically inhibited when treated with a high dose of CKI (2 mg/ mL, based on the total alkaloid concentration in CKI) and showed a dose-dependent effect (Figure 1A and Supplementary Figure 1A). An Annexin V/Propidium Iodide (PI) assay was used to quantify cell apoptosis when MCF-7 cells were treated with CKI. Percentage of apoptotic cells, particularly at the higher dose of CKI, was increased at both time points compared with untreated cells, indicating that apoptosis was induced in cells treated with CKI (Figure 1B and 1C). The caspase3/7 colorimetric assay also showed that there was increased caspase3/7 activity in cells treated with CKI (Supplementary Figure 1B). Altogether, these results showed that CKI could inhibit growth and induce apoptosis of MCF-7 cells in vitro.
Global gene expression changes in MCF-7 cells treated with CKI To further investigate the underlying molecular mechanisms of CKI on MCF-7 cells, we performed high-depth next generation sequencing using an Illumina HiSeq 2500. In total, more than 732 million stranded 100 basepairs (bp) paired-end reads were sequenced from 9 groups of MCF-7 cells treated with two doses of CKI or one dose of chemotherapy drug 5-Fluorouracil (5-FU) for 24 and 48 hours along with untreated cells (Supplementary Table 1) (GSE78512). The global gene expression profiles of CKI treated cells, particularly in cells treated with high dose CKI (2 mg/mL), were clearly different from the profile of 5-FU treated cells compared with untreated cells (Supplementary Figure 2). We then used edgeR to identify the statistically significant differentially expressed (DE) genes for the pairwise comparisons between cells treated with 1 mg/mL CKI, 2 mg/mL CKI and 5-FU for 24 or 48 hours respectively (Figure 2 and Supplementary Table 2). Compared with untreated cells, fewer than 200 genes had significantly altered expression in cells treated with low dose CKI (1 mg/mL) for 24 or 48 hours (Figure 2A and 2B). However, many more DE genes (1,826 genes for 24 hours and 2,904 for 48 hours) were identified in cells treated with high dose CKI (2 mg/mL). Interestingly, when comparing the number of DE genes in cells treated with high dose CKI with low dose CKI, we observed almost twice as many genes down-regulated but only a small number of genes (828 to 791) up-regulated (Figure 2A and 2B). Furthermore, we compared DE genes in cells treated with high dose CKI and in cells treated with 5-FU (Supplementary Figure 3). For up-regulated genes in cells treated with high dose CKI for 24 hours, approximately half (396 out of 791) of these were also identified as DE genes, with most (384) being upregulated in 5-FU treated cells as well. 459 down-regulated genes were also shown as DE genes with most of these (424 out of 459) also being down-regulated in cells treated with 5- FU for 24 hours (Supplementary Figure 3A). After cells were treated with CKI or 5-FU for 48 hours, the number
RESULTS CKI inhibits MCF-7 cell proliferation and induces cell apoptosis To characterise the effect of CKI on proliferation of MCF-7 breast cancer cells, we used the XTT assay to measure cell viability after treating with different doses of www.impactjournals.com/oncotarget
66004
Oncotarget
of DE genes decreased dramatically in 5-FU treated cells, but greatly increased in cells treated with 2 mg/mL CKI (Supplementary Figure 3B). The common DE genes altered by CKI or 5-FU showed consistent expression changes at 48 hours (Supplementary Figure 3B). To validate the gene expression changes from transcriptome analysis, we performed quantitative PCR (qPCR) for 6 genes and acquired overall consistent results (Figure 2C, Supplementary Figure 4 and Supplementary Table 2).
GO terms were clustered into several primary categories, including “Regulation of biological process, cellular process and metabolic process”, “Cell differentiation, development”, “Transport, localisation”, “Chromatin organisation, organelle organisation”, “Cell motility and migration” and “Secondary metabolic processes and reactive oxygen species metabolic”. Interestingly, we found that the majority of cell growth or proliferation related GO terms included more down-regulated genes, while GO terms associated with “Secondary metabolic processes and reactive oxygen species metabolic” showed enrichment of more up-regulated genes (Figure 3A). In MCF-7 cells treated with CKI for 48 hours, similar categories of over-represented GO terms seen at 24 hours were also observed, such as “Metabolic process”, “Regulation of metabolic process” and “Localization”. In addition, cell proliferation related terms, including “Cell cycle”, “Cell growth” and “Cell death” were also overrepresented in DE genes from cells treated with CKI for 48 hours (Figure 3B). Furthermore, we compared the overrepresentation of GO terms of the 200 most significantly
Annotation of the molecular pathways altered by CKI in MCF-7 cells Since CKI likely contains multiple bioactive ingredients, we used a number of systems biology methods to explore the molecular mechanisms of CKI. The over-represented Gene Ontology (GO) terms for all DE genes identified in cells treated with high dose CKI (2 mg/mL) for 24 hour and 48 hours are shown in Figure 3A and 3B. Based on their functional similarity, these
Figure 1: CKI inhibits proliferation and induces apoptosis of MCF-7 cells. A. Inhibition of MCF-7 cell proliferation with CKI
treatment. The level of viability of cells under different treatments was measured using XTT:PMS. Data are represented as mean ±SEM (n=6). B. and C. Induction of apoptosis in MCF-7 cells with CKI treatment. The level of apoptosis was determined by measuring the levels of Annexin V and PI staining: B) Percentages of Annexin V+/PI+ cells, and C) representative plots of Annexin V and PI staining. Data are represented as mean ±SEM (n=6). Statistical analyses were performed using A) two-way ANOVA or B) t-test comparing with “untreated” (*p
